Dec 03, 2024  
2014-2015 Graduate Academic Catalog 
    
Catalog Navigation
  Catalog Home
  Academic Calendar
  University Overview
  Graduate and Professional Education
  Graduate Admission Requirements
  Academic Regulations and Policies
  Student Accounts, Fees and Financial Aid
  Services and Resources for Graduate Students
  Academic Departments, Graduate Degree Programs and Certificates
  Degree Programs and Certificates
  Course Descriptions
  Board of Regents, Academic Administration and Faculty
  Campus Map
  My Portfolio
HELP
2014-2015 Graduate Academic Catalog [ARCHIVED CATALOG]

Facebook this Page (opens a new window)
Tweet this Page (opens a new window)
Add to Portfolio (opens a new window)

EV 710 - Environmental Statistics and Modeling

3 lecture hours 0 lab hours 3 credits
Course Description
This course covers topics in statistics needed for the statistical analyses of water, air, and other environmental systems. It also presents methods for developing statistical models. Specific topics include: (1) determining if significant differences exist between data sets using parametric and non-parametric methods, (2) experimental design, (3) constructing linear and non-linear regression models, (4) developing Monte Carlo models, (5) analyzing time-series, and (6) special topics. Offered Fall term. (prereq: underGraduate course in introductory probability and statistics Graduate standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• Compare two or more treatments or data sets for differences using the t-test, non-parametric tests, or analysis of variance (ANOVA)
• Assess the effects of one or more variables on the response of a system using full and fractional factorial designs
• Design testing programs to control the probability of Type I and Type II errors
• Build mathematical models of systems using linear and non-linear regression analysis, and time series analysis
• Create artificial data sets suitable for modeling purposes using Monte Carlo simulation
• Utilize the JMP statistical package with facility to perform statistical analysis
Prerequisites by Topic
• None appended
Course Topics
• Review of statistics and definitions
• Data visualization, estimating percentiles
• Software introduction and use
• Assessing differences between data using parametric and non-parametric tests
• Assessing differences between data using analysis of variance (ANOVA)
• Discuss final project.
• Experimental design: Design testing programs to control the probability of Type I and Type II errors
• Building models using linear regression, parsimony
• Transformations, problems with linearization
• Building models using non-linear regression, joint confidence region
• Midterm exam
• Experimental Design:
• Measuring the effects of variables on an outcome using full and fractional factorial designs.
• Smoothing, Time series analysis,
• Auto and partial auto-correlations
• Identifying distributions, Monte Carlo simulation
• Review for Final Exam
• Final Exam
Laboratory Topics
• No laboratory topics appended.
Coordinator
William Gonwa


Facebook this Page (opens a new window)
Tweet this Page (opens a new window)
Add to Portfolio (opens a new window)